Investigation into actions of Xiebai and Zengye decoction on cough sensitivity, airway inflammation and gut microbiota in the rat model of post-infectious cough.

This work was undertaken to observe therapeutic effect of Xiebai and Zengye (XBZY) decoction on post-infectious cough (PIC) in rats, as well as its effect on gut microbiota and the exploration of the intestinal microecological mechanisms of XBZY decoction in the treatment of PIC. Using a random number table, the rats that were successfully modelled were assigned to the PIC, XBZY group (14.8 g/kg/d), and montelukast sodium treatment (MAS) group (1 mg/kg/d). The cough sensitivity of rats and changes in fecal water content were assessed, and serum interleukin-8 (IL-8) and tumor necrosis factor-alpha (TNF-α) levels were determined by ELISA. The histopathological changes in the bronchus and colon tissues were observed under the microscope after hematoxylin-eosin staining. Short-chain fatty acids (SCFAs) in fecal samples were measured by gas chromatography, and changes in gut microbiota were observed using 16S rRNA sequencing. The PIC rats showed decreased fecal water content, increased cough sensitivity, elevated serum TNF-α and IL-8 levels, and higher bronchitis scores comparing to normal control group. The PIC rats showed reductions in SCFAs and significant changes in the structure of gut microbiota. XBZY decoction intervention led to increased fecal water content in rats, reduced cough sensitivity, decreased serum IL-8 and TNF-α levels, decreased bronchitis scores, and alleviated inflammatory cell infiltration was observed in the colonic mucosa. Additionally, elevated SCFAs levels were observed in the PIC rats. XBZY decoction intervention improved alpha-/beta-diversity, and corrected microbiota imbalance in PIC rats. SCFAs, TNF-α and IL-8, acetic acid was revealed to be positively associated with Allobaculum but inversely correlated with unclassified_f_Oscillospiraceae; propanoic acid was positively associated with Lactobacilli but negatively associated with Romboutsia; butanoic acid exhibited positive correlations with Akkermansia and Lactobacilli, but negative correlations with unclassified_f_Oscillospiraceae, Eubacterium_xylanophilum_group, and Lachnospiraceae_NK4A136_group; Additionally, TNF-α was inversely linked to Allobaculum, while IL-8 was positively related to Romboutsia and Turicibacter. In conclusion, XBZY decoction significantly reduced cough sensitivity and airway inflammation in PIC rats while ameliorating stool dryness and colonic inflammation. The protective effects of XBZY decoction could be linked to modulat gut microbiota in PIC rats, and regulat SCFAs contents in PIC rats, while the regulator mechanisms of XBZY decoction in gut microbiota still requires further in-depth investigation.

Multi-relational graph convolutional networks: Generalization guarantees and experiments.

The class of multi-relational graph convolutional networks (MRGCNs) is a recent extension of standard graph convolutional networks (GCNs) to handle heterogenous graphs with multiple types of relationships. MRGCNs have been shown to yield results superior than traditional GCNs in various machine learning tasks. The key idea is to introduce a new kind of convolution operated on tensors that can effectively exploit correlations exhibited in multiple relationships. The main objective of this paper is to analyze the algorithmic stability and generalization guarantees of MRGCNs to confirm the usefulness of MRGCNs. Our contributions are of three folds. First, we develop a matrix representation of various tensor operations underneath MRGCNs to simplify the analysis significantly. Next, we prove the uniform stability of MRGCNs and deduce the convergence of the generalization gap to support the usefulness of MRGCNs. The analysis sheds lights on the design of MRGCNs, for instance, how the data should be scaled to achieve the uniform stability of the learning process. Finally, we provide experimental results to demonstrate the stability results.

Astragaloside IV Regulates Insulin Resistance and Inflammatory Response of Adipocytes via Modulating CTRP3 and PI3K/AKT Signaling.

INTRODUCTION: Emerging evidence showed that adipocytes are important regulators in controlling insulin resistance in type 2 diabetes mellitus (T2DM). So far, compounds isolated from natural plants have been widely studied for their roles in alleviating T2DM-associated complications. This work evaluated the actions of astragaloside IV (AS-IV) on insulin resistance and inflammatory biomarker expression in adipocytes and explored the potential mechanisms. METHODS: Glucose consumption of the adipocytes was determined by a glucose assay kit; the mRNA expression levels of glucose transporter type 4 (GLUT-4), interleukin-6 (IL-6), TNF-α and C1q tumor necrosis factor-related protein 3 (CTRP3) were measured by quantitative real-time PCR (qRT-PCR); the protein levels were determined by western blot assay and enzyme-linked immunosorbent assay. RESULTS: AS-IV concentration-dependently increased glucose consumption in the insulin resistance adipocytes. Further qRT-PCR results showed that AS-IV concentration-dependently reduced adipocyte IL-6 and TNF-α expression. Moreover, GLUT-4 expression in adipocytes was also significantly upregulated by AS-IV. Furthermore, we found that AS-IV concentration-dependently increased CTRP3 expression in adipocytes. CTRP3 silence decreased glucose consumption, upregulated IL-6 and TNF-α expression and downregulated GLUT-4 mRNA expression in 200 µM AS-IV-treated adipocytes. Moreover, AS-IV treatment enhanced the activity of phosphoinositide 3-kinase (PI3K)/AKT signaling in adipocytes, which was markedly attenuated by CTRP3 silencing. Importantly, inhibition of PI3K/AKT signaling also attenuated AS-IV induced an increase in glucose consumption and GLUT-4 expression and a decrease in IL-6 and TNF-α expression of adipocytes. CONCLUSIONS: Collectively, our data indicated that AS-IV attenuated insulin resistance and inflammation in adipocytes via targeting CTRP3/PI3K/Akt signaling.

LS-NTP: Unifying long- and short-range spatial correlations for near-surface temperature prediction.

The near-surface temperature prediction (NTP) is an important spatial-temporal forecast problem, which can be used to prevent temperature crises. Most of the previous approaches fail to explicitly model the long- and short-range spatial correlations simultaneously, which is critical to making an accurate temperature prediction. In this study, both long- and short-range spatial correlations are captured to fill this gap by a novel convolution operator named Long- and Short-range Convolution (LS-Conv). The proposed LS-Conv operator includes three key components, namely, Node-based Spatial Attention (NSA), Long-range Adaptive Graph Constructor (LAGC), and Long- and Short-range Integrator (LSI). To capture long-range spatial correlations, NSA and LAGC are proposed to evaluate node importance aiming at auto-constructing long-range spatial correlations, which is named as Long-range aware Graph Convolution Network (LR-GCN). After that, the Short-range aware Convolution Neural Network (SR-CNN) accounts for the short-range spatial correlations. Finally, LSI is proposed to capture both long- and short-range spatial correlations by intra-unifying LR-GCN and SR-CNN. Upon the proposed LS-Conv operator, a new model called Long- and Short-range for NPT (LS-NTP) is developed. Extensive experiments are conducted on two real-world datasets and the results demonstrate that the proposed method outperforms state-of-the-art techniques. The source code is available on GitHub:https://github.com/xuguangning1218/LS_NTP.

Skin Permeation of Solutes from Metalworking Fluids to Build Prediction Models and Test A Partition Theory.

Permeation of chemical solutes through skin can create major health issues. Using the membrane-coated fiber (MCF) as a solid phase membrane extraction (SPME) approach to simulate skin permeation, we obtained partition coefficients for 37 solutes under 90 treatment combinations that could broadly represent formulations that could be associated with occupational skin exposure. These formulations were designed to mimic fluids in the metalworking process, and they are defined in this manuscript using: one of mineral oil, polyethylene glycol-200, soluble oil, synthetic oil, or semi-synthetic oil; at a concentration of 0.05 or 0.5 or 5 percent; with solute concentration of 0.01, 0.05, 0.1, 0.5, 1, or 5 ppm. A single linear free-energy relationship (LFER) model was shown to be inadequate, but extensions that account for experimental conditions provide important improvements in estimating solute partitioning from selected formulations into the MCF. The benefit of the Expanded Nested-Solute-Concentration LFER model over the Expanded Crossed-Factors LFER model is only revealed through a careful leave-one-solute-out cross-validation that properly addresses the existence of replicates to avoid an overly optimistic view of predictive power. Finally, the partition theory that accompanies the MCF approach is thoroughly tested and found to not be supported under complex experimental settings that mimic occupational exposure in the metalworking industry.

A novel combination of quick response code and microfluidic paper-based analytical devices for rapid and quantitative detection.

Nowadays, there is great interest in the use of microfluidic paper-based analytical devices (µPADs) for low-cost diagnostics. In most cases, the test equipment is needed. Here we report a new type of device-independent detection method based on timer-paper-based analytical devices, which can be tested by smartphone, and its application for cholesterol detection. The Quick Response code was designed as the timer component of this device. Wax printing method was employed to print the pattern on filter paper. The color and enzyme reagents have been immobilized in the hydrophilic channel to complete the colorimetric detection for cholesterol. Under laminar flow conditions of the cellulose network, the liquid volume of detection zone has been quantified by monitoring the fluid residence time on different area of the timer-paper-based devices. The precise monitoring of detection time can promote the accuracy of colorimetric detection. This is very important for the quantitative detection of paper-based analytical devices. One significant outcome of this report is that simple and accurate timer can be used for detection process self-clocking. The factors of total detection time have been investigated. The linear range of the calibration curve was 3.0 ~ 6.0 mmol L-1, with correlation coefficient of 0.9956. With the characteristic of easy to use, low cost and accurate monitoring of detection time, this kind of timer-paper-based devices can be applied to cholesterol or other substances rapid detection.

Human GSTs polymorphisms in the Hakka population of south China and their associations with family history of several chronic diseases.

OBJECTIVE: To investigate the associations of genetic polymorphisms in GSTs genes of the Hakka population of south China with family histories of certain chronic diseases. METHODS: Five hundred and thirty-nine healthy Hakka natives of Meizhou city of Guangdong province in south China were involved. The genotypes of GSTM1, GSTT1, GSTP1, GSTM3, and GSTA1 were determined using PCR and restriction fragment length polymorphism analysis. The observed polymorphisms were analyzed by Chi-square and Hardy-Weinberg equilibrium tests. Logistic regression analysis was used to determine the associations of the distributions of GST genotypes with family history of certain chronic diseases. RESULTS: The distributions of polymorphisms in GSTP1, GSTM3, and GSTA1 conformed to the Hardy-Weinberg equilibrium. Compared to the Cantonese, the Hakka had a lower distribution of the GSTM3 deletion genotype (3.15% vs. 11.9%). A weak association was observed between the GSTM1 genetic polymorphism and family history of hypertension. Alcohol drinkers had a higher frequency of the null-GSTM1 genotype, while smokers had a higher frequency of a variant GSTP1 genotype. CONCLUSION: The results suggest that the Hakka is a special and distinctive Han Chinese ethnic group with different GSTs genetic polymorphisms. Smoking and drinking might be related to the distribution of GST genotypes.

[Study on the genetic polymorphisms of human glutathione-S-transferase A1 in Hakka population in South China].

OBJECTIVE: Glutathione-S-transferase A1 (GSTA1) is one of the major phase II detoxification enzymes in the cytosol, which genetic polymorphisms distribution is different in different ethnic, national and regional population. Up to now, GSTA1 genetic polymorphisms has been rarely reported in China. The purpose of the study was to investigate the distribution of genetic polymorphisms of human GSTA1 in Hakka population in South China. METHODS: Polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) were used to identify the genotypes of GSTA1 gene and the data were analyzed with SPSS10.0 software. RESULTS: The GSTA1 genetic polymorphisms were detected in 480 samples. The frequency of GSTA1 * A/ * A,GSTA1 * A/ * B and GSTA1 * B/ * B were 77.1%, 21.7% and 1.2% respectively. And the GSTA1 genetic polymorphism distribution was in accordance with the Hardy-Weinberg equilibrium rule. There were no difference in the GSTA1 genetic polymorphisms among the different groups of age or gender. Logistic regression analysis showed that there were no association between the GSTA1 genetic polymorphism and family history of hypertension, coronary heart disease, stroke, lung cancer and nasopharyngeal cancer, et al. CONCLUSION: The GSTA1 gene existed polymorphism among Hakka in South China.